What i'm learning is just because something might be hard to you or I, doesn't mean it's not possible or not working. LLMs can generlaly only do what they have

What i'm learning is just because something might be hard to you or I, doesn't mean it's not possible or not working. LLMs can generlaly only do what they have data on, either in training, or instructions via prompting it seems. Keeping instructions reliable, is increasing and testing, appears to benefit from LLMops tools like Agenta, etc. It seems to me like LLMs are reasonably well suited for things that code can't do easily as well. You can find models on Hugging face that are great at categorizing and applying labels and categorization, instead of trying to get a generalized assistant model to do it. I'm more and more looking at tools like OpenRouter to allow doing each step with the model that does it best, almost functionally where needed to increase stability. For now, it seems to be one way to improve reliability dramatically, happy to learn about what others are finding too. It seems like a pretty nascent area still where existing tooling in other areas of tech is still figuring itself out in the LLM space.